Lab course materials for IEMBA 8/9 course "Coding and Artificial Intelligence"

Overview

IEMBA 8/9 - Coding and Artificial Intelligence

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Dear IEMBA 8/9 students,

welcome to our IEMBA 8/9 elective course Coding and Artificial Intelligence, taught by Prof. Dr. Damian Borth and Prof. Dr. Barbara Weber. In this course, lectures and hands-on lab courses alternate to provide a better learning experience. Lab course materials for Python programming, Machine Learning und Deep Learning are available in and accessible through this repository.

Please use a laptop computer for the lab courses (not a tablet) to be able to fully participate in the exercises.

Happy Coding!

Your IEMBA teaching team


This table lists all coding lab notebooks and exercise notebooks:

Date Topic Lab Notebook Exercise Notebook Solution Notebook
< Mon, Jan 17 Prerequisite - Binder
Open In Colab
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Mon, Jan 17 Python 101: Jupyter Notebooks and Python Basics Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Tue, Jan 18, morning session Python 102: Numerical Math & Images Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Tue, Jan 18, afternoon session Machine Learning I
(Naive Bayes)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Tue, Jan 18, afternoon session Machine Learning II
(k Nearest-Neighbors)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Wed, Jan 19, morning session Deep Learning I
(Artificial Neural Nets)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
Wed, Jan 19, afternoon session Deep Learning II
(Convolutional Neural Nets)
Binder
Open In Colab
Binder
Open In Colab
Binder
Open In Colab
< TBD Exam Exercise - Binder
Open In Colab
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Owner
Artificial Intelligence & Machine Learning (AI:ML Lab) @ HSG
Deep Learning Research by AIML Team @ HSG
Artificial Intelligence & Machine Learning (AI:ML Lab) @ HSG
A Python Package for Convex Regression and Frontier Estimation

pyStoNED pyStoNED is a Python package that provides functions for estimating multivariate convex regression, convex quantile regression, convex expect

Sheng Dai 17 Jan 08, 2023
PyTorch reimplementation of hand-biomechanical-constraints (ECCV2020)

Hand Biomechanical Constraints Pytorch Unofficial PyTorch reimplementation of Hand-Biomechanical-Constraints (ECCV2020). This project reimplement foll

Hao Meng 59 Dec 20, 2022
FFTNet vocoder implementation

Unofficial Implementation of FFTNet vocode paper. implement the model. implement tests. overfit on a single batch (sanity check). linearize weights fo

Eren Gölge 81 Dec 08, 2022
Keras-tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation(Unfinished)

Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas

645 Dec 29, 2022
Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline

Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline. The pipeline accepts english text as input and returns the French translation.

Afropunk Technologist 1 Jan 24, 2022
Combinatorially Hard Games where the levels are procedurally generated

puzzlegen Implementation of two procedurally simulated environments with gym interfaces. IceSlider: the agent needs to reach and stop on the pink squa

Autonomous Learning Group 3 Jun 26, 2022
A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners

Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati

Aritra Roy Gosthipaty 59 Dec 10, 2022
Customizable RecSys Simulator for OpenAI Gym

gym-recsys: Customizable RecSys Simulator for OpenAI Gym Installation | How to use | Examples | Citation This package describes an OpenAI Gym interfac

Xingdong Zuo 14 Dec 08, 2022
[NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”,

Improving Contrastive Learning on Imbalanced Data via Open-World Sampling Introduction Contrastive learning approaches have achieved great success in

VITA 24 Dec 17, 2022
[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training

RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p

Yu Meng 60 Dec 30, 2022
Plover-tapey-tape: an alternative to Plover’s built-in paper tape

plover-tapey-tape plover-tapey-tape is an alternative to Plover’s built-in paper

7 May 29, 2022
Generate high quality pictures. GAN. Generative Adversarial Networks

ESRGAN generate high quality pictures. GAN. Generative Adversarial Networks """ Super-resolution of CelebA using Generative Adversarial Networks. The

Lieon 1 Dec 14, 2021
New approach to benchmark VQA models

VQA Benchmarking This repository contains the web application & the python interface to evaluate VQA models. Documentation Please see the documentatio

4 Jul 25, 2022
Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic Segmentation (CVPR 2022)

CCAM (Unsupervised) Code repository for our paper "CCAM: Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localizati

Computer Vision Insitute, SZU 113 Dec 27, 2022
TorchX: A PyTorch Extension Library for More Efficient Deep Learning

TorchX TorchX: A PyTorch Extension Library for More Efficient Deep Learning. @misc{torchx, author = {Ansheng You and Changxu Wang}, title = {T

Donny You 8 May 28, 2022
Trained on Simulated Data, Tested in the Real World

Trained on Simulated Data, Tested in the Real World

livox 43 Nov 18, 2022
A hifiasm fork for metagenome assembly using Hifi reads.

hifiasm_meta - de novo metagenome assembler, based on hifiasm, a haplotype-resolved de novo assembler for PacBio Hifi reads.

44 Jul 10, 2022
An implementation of the 1. Parallel, 2. Streaming, 3. Randomized SVD using MPI4Py

PYPARSVD This implementation allows for a singular value decomposition which is: Distributed using MPI4Py Streaming - data can be shown in batches to

Romit Maulik 44 Dec 31, 2022
Code for the paper "Relation of the Relations: A New Formalization of the Relation Extraction Problem"

This repo contains the code for the EMNLP 2020 paper "Relation of the Relations: A New Paradigm of the Relation Extraction Problem" (Jin et al., 2020)

YYY 27 Oct 26, 2022
Optical machine for senses sensing using speckle and deep learning

# Senses-speckle [Remote Photonic Detection of Human Senses Using Secondary Speckle Patterns](https://doi.org/10.21203/rs.3.rs-724587/v1) paper Python

Zeev Kalyuzhner 0 Sep 26, 2021